改进粒子群算法求解GPS短基线整周模糊度的研究

RESEARCH ON AMBIGUITY RESOLUTION OF GPS SHORT BASELINE BY USING IMPROVED PARTICLE SWARM OPTIMIZATION

针对降相关处理的模糊度浮点解及其方差阵,提出了一种基于改进粒子群算法(IPSO)的模糊度搜索新方法。IPSO以实数编码取整的方式对双差模糊度进行编码,并通过自适应计算惯性权重和粒子变异,改善了标准粒子群算法(PSO)的全局收敛性和稳健性,极大地提高了模糊度解算的成功率。通过与LAMBDA法和遗传算法的对比,验证了新方法具有快速、可靠等特点,在模糊度求解方面具有良好的应用价值。

Aimming at the ambiguity float solution of reducing the correlation and its variance arrary,a new ambiguity search algorithm based on improved particle swarm optimization（IPSO） was proposed.For the integer nature of double difference ambiguity,real code were modified to round in coding and made up of particle individual.Through adaptive calculation of inertia weight and particle mutation,IPSO has improved the global convergence and robustness of standard particle swarm optimization to search carrier phase integer ambiguity.The testing example indicates that the new method not only increased the success rate of fixing ambiguity,but also improved the search efficiency,and it spent the same amount of time with LAMBDA,and less time than that genetic algorithm did.The new method is fast and reliable,and will make great application significance to ambiguity resolution of GPS short-baseline.